Classifying Movies Based on Audience Perceptions: MTI Framework and Box Office Performance

Ji-Hyun Shon, Young-Gul Kim and Sang-Jin Yim

Journal of Media Economics, 2014, vol. 27, issue 2, 79-106

Abstract: This research examined the current status of the movie genre usage in movie research and film industry and introduced a new method to classify movies. Using a large-scale audience survey data, the authors clustered movies into 9 distinct types based on 8 audience-perceived movie characteristics such as fun, eye-catching, discomfort, and feel-good. The authors validated their method by comparing movie types vs. movie genres in terms of their box-office revenue explanatory power. All three types of box-office revenues (opening week revenue, total revenue, revenue-per-screen) differed significantly across movie types, whereas only the opening week revenue showed a significant difference across movie genres, suggesting that movie types may be a better predictor of a movie's box-office performance than movie genres that have been frequently used in prior research on box-office performance prediction.

Date: 2014
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DOI: 10.1080/08997764.2014.903959

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